About The Position

Peloton is seeking a Senior Production Engineer with deep oil & gas operations experience to help validate AI-generated production engineering outputs and support the development of AI-assisted operational workflows. This role will work closely with software developers, and our clients to ensure AI-generated recommendations align with real-world production engineering practices, field constraints, and operational reliability standards. The ideal candidate brings strong expertise in production optimization, production surveillance, decline analysis, artificial lift systems, and operational troubleshooting.

Requirements

  • 10+ years of production engineering experience in oil & gas operations
  • Strong background in production optimization and surveillance
  • Experience supporting field operations and production troubleshooting
  • Strong understanding of decline analysis, forecasting, and artificial lift systems
  • Experience working cross-functionally with engineering, operations, and technical teams
  • Strong analytical and operational problem-solving skills
  • Familiarity with production data systems and operational reporting tool

Nice To Haves

  • Experience supporting AI, analytics, or digital transformation initiatives
  • Familiarity with AI-assisted operational workflows or engineering validation processes
  • Experience reviewing automated production optimization recommendations

Responsibilities

  • Work with developers and technical teams to define expected engineering and operational outputs
  • Validate AI-generated production optimization recommendations and operational workflows
  • Review AI-assisted production forecasts, decline curve analysis, and surveillance outputs
  • Ensure recommendations align with field operations, facility constraints, and production engineering best practices
  • Apply production engineering expertise to identify operational anomalies, underperforming wells, and optimization opportunities
  • Support development of engineering validation criteria and quality control processes for AI-generated outputs
  • Evaluate AI-generated root cause analysis and operational recommendations for technical accuracy
  • Collaborate with operations and technical teams to improve AI-assisted production workflows and operational reliability
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